def plot_comparison(f1, f2, data, xs=[-0.5, 7], ys=[-400, 1000], s=0):
'''Compare file 1 (red) with file 2 (blue), taking the mean and std
of the signal'''
d = handler.extract_data(f1)
d2 = handler.extract_data(f2)
# due to the 60Hz noise of the water heater, I have to filter it out with a notch filter
temp = np.array([56.0,64.0])/(d['fs']/2.0)
# 3 is the highest order I can go without it going crazy
b,a = butter(3, temp[0], btype='bandstop')
y = filtfilt(b,a,lowpass_filter((d['stim']*1e6, d['fs']))[0].T).T
y2 = filtfilt(b,a,lowpass_filter((d2['stim']*1e6, d2['fs']))[0].T).T
ystd = np.std(y, axis=1)
ymean = average((y, d['fs']))[0][:,0]
t = d['t']*1e3
y2std = np.std(y2, axis=1)
y2mean = average((y2, d2['fs']))[0][:,0]
t2 = d2['t']*1e3
plt.figure(figsize=(8,6))
plt.fill_between(t, (ymean-ystd), (ymean+ystd), alpha=0.5, facecolor=color_palette[0])
plt.plot(t, ymean, color=color_palette[0])
plt.fill_between(t2, y2mean - y2std, y2mean + y2std, alpha=0.5, facecolor=color_palette[5])
plt.plot(t2, y2mean, color=color_palette[5])
plt.xlim(xs)
plt.ylim(ys)
plt.ylabel('Voltage (µV)')
plt.xlabel('Time (ms)')
plt.title(descriptive_title(f1).replace('<br>', '\n'))
plt.legend([str(handler.get_current(data,f1))+'µA', str(handler.get_current(data,f2))+'µA'])
if s and type(s) == str:
plt.savefig(s + '.pdf')
elif s:
plt.savefig(f1[:-4]+ f2[:-4]+'-comaparison.pdf')
def generate_tiled_plot(filelabel, tile=True, factor=50):
plot_data = []
t = None
func = compose(average, lowpass_filter)
for i, (l, f) in enumerate(filelabel):
offset = i * factor if tile else 0
data = handler.extract_data(f)
if type(t) == type(None):
t = data['t']
y, fs = func((data['stim'], data['fs']))
plot_data += [Scatter(x=t*1e3, y=y[:,0]*1e6 + offset, name=str(l), line=dict(width=2))]
fig = {'data': plot_data}
fig['layout'] = dict(
title='Current-response comparison',
xaxis=dict(title='Time (ms)'),
yaxis=dict(title='Current increasing -->')
)
return fig
def generate_tiled_plot(filelabel, tile=True, factor=50):
plot_data = []
t = None
func = compose(average, lowpass_filter)
for i, (l, f) in enumerate(filelabel):
offset = i * factor if tile else 0
data = handler.extract_data(f)
if type(t) == type(None):
t = data['t']
y, fs = func((data['stim'], data['fs']))
plot_data += [
Scatter(x=t * 1e3,
y=y[:, 0] * 1e6 + offset,
name=str(l),
line=dict(width=2))
]
fig = {'data': plot_data}
fig['layout'] = dict(title='Current-response comparison',
xaxis=dict(title='Time (ms)'),
yaxis=dict(title='Current increasing -->'))
return fig
